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A rapidly warming climate is driving changes in biodiversity worldwide, and its impact on insect communities is critical given their outsized role in ecosystem function and services. We use a long‐term dataset of North American bumble bee species occurrences to determine whether the community temperature index (CTI), a measure of the balance of warm‐ and cool‐adapted species in a community, has increased given warming temperatures. CTI has increased by an average of 0.99°C in strong association with warming maximum summer temperatures over the last 30 years with the areas exhibiting the largest increases including mid‐ to high latitudes as well as low and high elevations—areas relatively shielded from other intensive global changes. CTI shifts have been driven by the decline of cold‐adapted species and increases in warm‐adapted species within bumble bee communities. Our results show the pervasive impacts and ecological implications warming temperatures pose to insects. [ABSTRACT FROM AUTHOR]

Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud-based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

CSBC is the biggest scientific event dedicated to computing in Latin America, integrating Brazilian computing and driving the area in the country. In one of its satellite events, WCAMA combines computing with the management of the environment and natural resources, an essential theme for Brazil. The analysis of the last eleven years of WCAMA (2013 – 2023) exposes a relevance in the theme of beekeeping, it also notes a limited number of broad collaborations, with the most prolific authors in a low number of collaborations. Several collaborations transcend national universities, involving environmental institutes or international institutions.

Population cycles have been observed in mammals as well as insects, but consistent population cycling has rarely been documented in agroecosystems and never for a beetle. We analysed the long-term population patterns of the cabbage stem flea beetle Psylliodes chrysocephala in winter oilseed rape over 50 years. Psylliodes chrysocephala larval density from 3045 winter oilseed rape fields in southern Sweden showed strong 8-year population cycles in regional mean density. Fluctuations in larval density were synchronous over time across five subregional populations. Subregional mean environmental variables explained 90.6% of the synchrony in P. chrysocephala populations at the 7-11 year time-scale. The number of days below -10°C showed strong anti-phase coherence with larval densities in the 7-11 year time-scale, such that more cold days resulted in low larval densities. High levels of the North Atlantic Oscillation weather system are coherent and anti-phase with cold weather in Scania, Sweden. At the field-scale, later crop planting date and more cold winter days were associated with decreased overwintering larval density. Warmer autumn temperatures, resulting in greater larval accumulated degree days early in the season, increased overwintering larval density. Despite variation in environmental conditions and crop management, 8-year cycles persisted for cabbage stem flea beetle throughout the 50 years of data collection. Moran effects, influenced by the North Atlantic Oscillation weather patterns, are the primary drivers of this cycle and synchronicity. Insect pest data collected in commercial agriculture fields is an abundant source of long-term data. We show that an agricultural pest can have the same periodic population cycles observed in perennial and unmanaged ecosystems. This unexpected finding has implications for sustainable pest management in agriculture and shows the value of long-term pest monitoring projects as an additional source of time-series data to untangle the drivers of population cycles.

Making paleoecological data accessible, usable, and useful to a global and diverse community of researchers, educators, and students across Earth sciences is an essential yet challenging task. Multiple data access and discovery tools must co-evolve with ever-changing user needs through an iterative, open-ecosystem software development approach. We employ a user-centered design study to evaluate one such ecosystem, the Neotoma Paleoecology Database, whose mission is to advance understanding of global-change processes by providing an expert-curated data resource. Neotoma contains over 11 million observations from 30,000 + datasets across 20,000 + sites, representing proxies of environmental and ecological conditions of the past. Neotoma comprises three interrelated software components – an interactive web mapping application, statistical programming package, and API – that provide different levels of functionality to different audiences. Although development efforts of these software components have involved the user community, Neotoma lacks a systematic evaluation process, which is important for informing the gap between perceived potential and actual utility. We address this knowledge gap using scenario-based design exercises and a usability/utility assessment. Major contributions include actionable insights for enhancing Neotoma's user experience and a user-centered design model that can be adapted to advance the development of other Earth and environmental science software ecosystems.

BACKGROUND: Rising global temperatures are associated with emerging insect pests, reflecting earlier and longer insect activity, faster development, more generations per year and changing species' ranges. Insecticides are often the first tools available to manage these new threats. In the southeastern US, sweet potato whitefly (Bemisia tabaci) has recently become the major threat to vegetable production. We used data from a multi‐year, regional whitefly monitoring network to search for climate, land use, and management correlates of whitefly activity. RESULTS: Strikingly, whiteflies were detected earlier and grew more abundant in landscapes with greater insecticide use, but only when temperatures were also relatively warm. Whitefly outbreaks in hotter conditions were not associated with specific active ingredients used to suppress whiteflies, which would be consistent with a regional disruption of biocontrol following sprays for other pests. In addition, peak whitefly detections occurred earlier in areas with more vegetable production, but later with more cotton production, consistent with whiteflies moving among crops. CONCLUSION: Altogether, our findings suggest possible links between warmer temperatures, more abundant pests, and frequent insecticide applications disrupting biological control, though this remains to be explicitly demonstrated. Climate‐initiated pesticide treadmills of this type may become an increasingly common driver of emerging pest outbreaks as global change accelerates. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

Making paleoecological data accessible, usable, and useful to a global and diverse community of researchers, educators, and students across Earth sciences is an essential yet challenging task. Multiple data access and discovery tools must co-evolve with ever-changing user needs through an iterative, open-ecosystem software development approach. We employ a user-centered design study to evaluate one such ecosystem, the Neotoma Paleoecology Database, whose mission is to advance understanding of global-change processes by providing an expertcurated data resource. Neotoma contains over 11 million observations from 30,000 + datasets across 20,000 + sites, representing proxies of environmental and ecological conditions of the past. Neotoma comprises three interrelated software components -- an interactive web mapping application, statistical programming package, and API -- that provide different levels of functionality to different audiences. Although development efforts of these software components have involved the user community, Neotoma lacks a systematic evaluation process, which is important for informing the gap between perceived potential and actual utility. We address this knowledge gap using scenario-based design exercises and a usability/utility assessment. Major contributions include actionable insights for enhancing Neotoma's user experience and a user-centered design model that can be adapted to advance the development of other Earth and environmental science software ecosystems. [ABSTRACT FROM AUTHOR]

A scientifically informed approach to decision-making is key to ensuring the sustainable management of ecosystems, especially in the light of increasing human pressure on habitats and species. Protected areas, with their long-term institutional mandate for biodiversity conservation, play an important role as data providers, for example, through the long-term monitoring of natural resources. However, poor data management often limits the use and reuse of this wealth of information. In this paper, we share lessons learned in managing long-term data from the Italian Alpine national parks. Our analysis and examples focus on specific issues faced by managers of protected areas, which partially differ from those faced by academic researchers, predominantly owing to different mission, governance, and temporal perspectives. Rigorous data quality control, the use of appropriate data management tools, and acquisition of the necessary skills remain the main obstacles. Common protocols for data collection offer great opportunities for the future, and complete recovery and documentation of time series is an urgent priority. Notably, before data can be shared, protected areas should improve their data management systems, a task that can be achieved only with adequate resources and a long-term vision. We suggest strategies that protected areas, funding agencies, and the scientific community can embrace to address these problems. The added value of our work lies in promoting engagement with managers of protected areas and in reporting and analysing their concrete requirements and problems, thereby contributing to the ongoing discussion on data management and sharing through a bottom-up approach. [ABSTRACT FROM AUTHOR]

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physio-logging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiologys informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from data as a noun (e.g., traits, counts) to data as a sentence, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally.

Abstract Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud‐based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

Diversifying agricultural landscapes may mitigate biodiversity declines and improve pest management. Yet landscapes are rarely managed to suppress pests, in part because researchers seldom measure key variables related to pest outbreaks and insecticides that drive management decisions. We used a 13-year government database to analyse landscape effects on European grapevine moth (Lobesia botrana) outbreaks and insecticides across c. 400 Spanish vineyards. At harvest, we found pest outbreaks increased four-fold in simplified, vineyard-dominated landscapes compared to complex landscapes in which vineyards are surrounded by semi-natural habitats. Similarly, insecticide applications doubled in vineyard-dominated landscapes but declined in vineyards surrounded by shrubland. Importantly, pest population stochasticity would have masked these large effects if numbers of study sites and years were reduced to typical levels in landscape pest-control studies. Our results suggest increasing landscape complexity may mitigate pest populations and insecticide applications. Habitat conservation represents an economically and environmentally sound approach for achieving sustainable grape production.

By definition, a smart city must improve its readiness for extreme events in order to confront the growing unpredictability of natural disasters. Doing this implies planning for resilience. That is, to enhance our capacity to cope, mitigate, adapt, and rebuild human settlements after a catastrophic event. Although scholars have argued that biodiversity can enhance resilience, there is a dearth of empirical research that specifically addresses this crucial issue. This research analyzes Nature's Contributions to People related to tsunami resilience. Then, the relationship between biodiversity and community resilience indexes is examined for 50 coastal Chilean cities that are prone to tsunamis, using biodiversity data from an open access database. The resilience index "population living in the first kilometer from the shoreline" was found to be correlated with species richness (p = 0.48) and the evenness biodiversity index, Pielou (p = −0.47). These results suggest that biodiversity data availability is crucial for understanding nature's contribution to human settlement resilience. Although this study was hindered by limited data availability, the potential use in other contexts remains valuable for the development of smart cities. The study highlights the need for increased biodiversity data collection on a national scale and emphasizes the use of ecoinformatics to create smart cities that can effectively respond to climate uncertainty in coastal urban areas. [ABSTRACT FROM AUTHOR]

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physiologging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiology’s informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from “data as a noun” (e.g., traits, counts) to “data as a sentence”, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally. [ABSTRACT FROM AUTHOR]

Variability in population densities is key to the ecology of natural systems but also has great implications for agriculture. Farmers' decisions are heavily influenced by their risk aversion to pest outbreaks that result in major yield losses. However, the need for long‐term pest population data across many farms has prevented researchers from exploring the drivers and implications of pest population variability (PV). Here, we demonstrate the critical importance of PV for sustainable farming by analyzing 13 years of pest densities across >1300 Spanish olive groves and vineyards. Variable populations were more likely to cause major yield losses, but also occasionally created temporal windows when densities fell below insecticide spray thresholds. Importantly, environmental factors regulating pest variability were very distinct from factors regulating mean density, suggesting variability needs to be uniquely managed. Finally, we found diversifying landscapes may be a win–win situation for conservation and farmers, as diversified landscapes promote less abundant and less variable pest populations. Therefore, we encourage agricultural stakeholders to increase the complexity of the landscapes surrounding their farms through conserving/restoring natural habitat and/or diversifying crops. [ABSTRACT FROM AUTHOR]

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physio-logging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiology’s informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from “data as a noun” (e.g., traits, counts) to “data as a sentence”, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally.

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long‐term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng‐Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time‐series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time‐series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine‐grained vegetation time‐series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology. [ABSTRACT FROM AUTHOR]

Are we entering a new ‘Golden Age’ of biogeography, with continued development of infrastructure and ideas? We highlight recent developments, and the challenges and opportunities they bring, in light of the snapshot provided by the 7th biennial meeting of the International Biogeography Society (IBS 2015). We summarize themes in and across 15 symposia using narrative analysis and word clouds, which we complement with recent publication trends and ‘research fronts’. We find that biogeography is still strongly defined by core sub-disciplines that reflect its origins in botanical, zoological (particularly bird and mammal), and geographic (e.g., island, montane) studies of the 1800s. That core is being enriched by large datasets (e.g. of environmental variables, ‘omics’, species’ occurrences, traits) and new techniques (e.g., advances in genetics, remote sensing, modeling) that promote studies with increasing detail and at increasing scales; disciplinary breadth is being diversified (e.g., by developments in paleobiogeography and microbiology) and integrated through the transfer of approaches and sharing of theory (e.g., spatial modeling and phylogenetics in evolutionary–ecological contexts). Yet some subdisciplines remain on the fringe (e.g., marine biogeography, deep-time paleobiogeography), new horizons and new theory may be overshadowed by popular techniques (e.g., species distribution modelling), and hypotheses, data, and analyses may each be wanting. Trends in publication suggest a shift away from traditional biogeography journals to multidisciplinary or open access journals. Thus, there are currently many opportunities and challenges as biogeography increasingly addresses human impacts on, and stewardship of, the planet (e.g., Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services). As in the past, biogeographers doubtless will continue to be engaged by new data and methods in exploring the nexus between biology and geography for decades into the future. But golden ages come and go, and they need not touch every domain in a discipline nor affect subdisciplines at the same time; moreover, what appears to be a Golden Age may sometimes have an undesirable ‘Midas touch’. Contexts within and outwith biogeography—e.g., methods, knowledge, climate, biodiversity, politics—are continually changing, and at times it can be challenging to establish or maintain relevance. In so many races with the Red Queen, we suggest that biogeography will enjoy greatest success if we also increasingly engage with the epistemology of our discipline.

An ecoinformatics approach was used to test how two noxious species in grapevines with varying host preferences and movement characteristics: the European grapevine moth (Lobesia botrana), and a parasitic fungus, the grape powdery mildew (Uncinula necator), are affected by local and landscape variables. Data were collected from 202 vineyards during four seasons: 2013, 2014, 2016 and 2017 and analysed using generalized mixed models. We hypothesized that the European grapevine moth would be affected most by the landscape variables, while the grape powdery mildew would be affected most by local ones. We found that the number of sprayings during the season was an important variable explaining variation in infestation levels between vineyards for both species. At the landscape scale, we found larger variations in the relationship between the studied variables and the two pests, but both were also affected by the surrounding land use including areas of deciduous orchards. Understanding the factors that affect the occurrence of various pests in the same environment might improve farmers' decision‐making. [ABSTRACT FROM AUTHOR]

Agricultural intensification is a key suspect among putative drivers of recent insect declines, but an explicit link between historical change in agricultural land cover and insect occurrence is lacking. Determining whether agriculture impacts beneficial insects (e.g. pollinators), is crucial to enhancing agricultural sustainability. Here, we combine large spatiotemporal sets of historical bumble bee and agricultural records to show that increasing cropland extent and decreasing crop richness were associated with declines in over 50% of bumble bee species in the agriculturally intensive Midwest, USA. Critically, we found that high crop diversity was associated with a higher occurrence of many species pre‐1950 even in agriculturally dominated areas, but that current agricultural landscapes are devoid of high crop diversity. Our findings suggest that insect conservation and agricultural production may be compatible, with increasing on‐farm and landscape‐level crop diversity predicted to have positive effects on bumble bees. [ABSTRACT FROM AUTHOR]

Ecological networks are increasingly studied at large spatial scales, expanding their focus from a conceptual tool for community ecology into one that also addresses questions in biogeography and macroecology. This effort is supported by increased access to standardized information on ecological networks, in the form of openly accessible databases. Yet, there has been no systematic evaluation of the fitness for purpose of these data to explore synthesis questions at very large spatial scales. In particular, because the sampling of ecological networks is a difficult task, they are likely to not have a good representation of the diversity of Earth's bioclimatic conditions, likely to be spatially aggregated, and therefore unlikely to achieve broad representativeness. In this paper, we analyse over 1300 ecological networks in the mangal.io database, and discuss their coverage of climates, and the geographic areas in which there is a deficit of data on ecological networks. Taken together, our results suggest that while some information about the global structure of ecological networks is available, it remains fragmented over space, with further differences by types of ecological interactions. This causes great concerns both for our ability to transfer knowledge from one region to the next, but also to forecast the structural change in networks under climate change. [ABSTRACT FROM AUTHOR]

Despite the 243,000 marine species described by 2022, our knowledge about the oceanic biodiversity is still incomplete. This knowledge gap carries potentially adverse and far-reaching consequences for the preservation of marine ecosystems, particularly in the context of the ongoing human-induced alterations to our biosphere and the rapid progression of climate change and global environmental shifts. Recently, however, a large number of online repositories have emerged, which catalogue, store and distribute biodiversity information, including taxonomic and species occurrence data. FishBase, the Global Biodiversity Information Facility (GBIF) and the Ocean Biodiversity Information System (OBIS) are part of these publicly available repositories representing a variety of sources that have exploded in number. However, despite the incredible accumulation of biodiversity records, not all the information is actually useful, nor does it represent any new knowledge regarding global species richness patterns. In this study, we assessed the spatial and temporal representativeness of marine fish records (order Actinopterygii) found in the GBIF and OBIS global repositories. The methodological framework that we developed relies on a series of non-parametric estimators for computing species richness from incidence data. This methodology employs hexagonal grids as sampling units that overlay marine bioregions across the globe. Using standard ecological and spatial analysis tools, we identify regions that are adequately represented in terms of available records and therefore have more reliable data, as well as regions with few records that do not represent current species richness. We overlap these results with the location of marine protected areas and fishing exploitation zones to understand the anthropogenic effect on marine ichthyofauna. We additionally evaluate hypotheses regarding the taxonomic, geographic, and temporal distribution of information biases to deepen our current understanding of public records of species occurrences worldwide. Considering that more than 40 years of information was analyzed, the results showed that, on a global scale, the primary data on marine fish available on GBIF and OBIS platforms are still far from being representative and complete. Only 1.14% of the records were useful for our analyses. In addition, we found that the information seems to be biased towards coastal areas, regions close to developed countries, and areas where there is a large fishing activity. Finally, the best represented species and families are those with a small body size, which use shallow habitats and are usually recognized as having commercial or cultural value. [ABSTRACT FROM AUTHOR]

Ecology documents and interprets the abundance and distribution of organisms. Ecoinformatics addresses this challenge by analyzing databases of observational data. Ecoinformatics of insects has high scientific and applied importance, as insects are abundant, speciose, and involved in many ecosystem functions. They also crucially impact human well-being, and human activities dramatically affect insect demography and phenology. Hazards, such as pollinator declines, outbreaks of agricultural pests and the spread insect-borne diseases, raise an urgent need to develop ecoinformatics strategies for their study. Yet, insect databases are mostly focused on a small number of pest species, as data acquisition is labor-intensive and requires taxonomical expertise. Thus, despite decades of research, we have only a qualitative notion regarding fundamental questions of insect ecology, and only limited knowledge about the spatio-temporal distribution of insects. We describe a novel high throughput cost-effective approach for monitoring flying insects as an enabling step toward “big data” entomology. The proposed approach combines “high tech” deep learning with “low tech” sticky traps that sample flying insects in diverse locations. As a proof of concept we considered three recent insect invaders of Israel’s forest ecosystem: two hemipteran pests of eucalypts and a parasitoid wasp that attacks one of them. We developed software, based on deep learning, to identify the three species in images of sticky traps from Eucalyptus forests. These image processing tasks are quite difficult as the insects are small (

Sweet oranges (Citrus sinensis (L.) Osbeck Sapindales: Rutaceae) dominated commercial citrus production in California until recently when there has been a shift to mandarins, mostly Citrus reticulata (Blanco) mandarins and Citrus clementina (hort. ex Tanaka) clementines. Past analyses of commercial field scouting and harvest data indicated that fork-tailed bush katydids (Scudderia furcata Brunner von Wattenwyl), a major pest in oranges, are present in clementine groves, but that fruit scarring attributed to katydids is rare. Conversely, jagged or web-like scarring attributed to caterpillars was more prevalent than expected. We used two field experiments in four representative cultivars of clementines to test four explanatory hypotheses for this observation: 1) katydids do not feed on clementine fruit, 2) damaged clementine fruit recover, 3) damaged clementine fruit preferentially abscise, and 4) katydid scars on clementine fruit have a different, undocumented morphology, not recognized as katydid damage. We find support for the latter two hypotheses. Katydids fed readily on the clementine fruit of all cultivars tested, chewing irregular holes that developed into jagged or web-like scars of a range of shapes and often led to splitting and abscission of maturing fruit. The katydid scars often more closely resembled chewing caterpillar damage than the round katydid scars in oranges, suggesting that katydid damage is being misclassified in clementines. The resistance documented in some other mandarins was not observed. Katydids are clearly a frugivorous pest causing previously unrecognized scarring in clementines. [ABSTRACT FROM AUTHOR]

SWEA-Dataveg is a vegetation-plot database collecting observations mainly in sub-Saharan Africa but also open to the rest of the African continent. To date this database contains more than 5,500 plot observations provided by 47 sources (projects, monographs, and articles). While the database is stored in PostgreSQL (including the PostGIS extension), the R-package "vegtable" implements a suitable exchange format. In this article we assess the current content of SWEA-Database and introduce its history and future as a repository of data for syntaxonomic assessments and macroecological research. [ABSTRACT FROM AUTHOR]

We report on the completed first volume of Vegetation Classification and Survey (VCS), which included ten Research Papers, six Short Database Reports, two Long Database Reports, two Forum Papers and one Report. We highlight three outstanding papers as examples of contributions of which we would like to see more in the future. Finally, we announce a new article type "VCS Methods" and report about the status of two upcoming Special Collections. Lists of colleagues who served as reviewers or linguistic editors in 2020 are included in appendices. [ABSTRACT FROM AUTHOR]

Recent decades have seen an explosion in the amount of data available on all aspects of biodiversity, which has led to data-driven approaches to understand how and why diversity varies in time and space. Global repositories facilitate access to various classes of species-level data including biogeography, genetics and conservation status, which are in turn required to study different dimensions of diversity. Ensuring that these different data sources are interoperable is a challenge as we aim to create synthetic data products to monitor the state of the world's biodiversity. One way to approach this is to link data of different classes, and to inventory the availability of data across multiple sources. Here, we use a comprehensive list of more than 200 000 marine animal species, and quantify the availability of data on geographical occurrences, genetic sequences, conservation assessments and DNA barcodes across all phyla and broad functional groups. This reveals a very uneven picture: 44% of species are represented by no record other than their taxonomy, but some species are rich in data. Although these data-rich species are concentrated into a few taxonomic and functional groups, especially vertebrates, data are spread widely across marine animals, with members of all 32 phyla represented in at least one database. By highlighting gaps in current knowledge, our census of marine diversity data helps to prioritize future data collection activities, as well as emphasizing the importance of ongoing sustained observations and archiving of existing data into global repositories. This article is part of the theme issue 'Integrative research perspectives on marine conservation'. [ABSTRACT FROM AUTHOR]

Taxonomic lists are crucial elements of vegetation-plot databases and provide the links between original entries, reference taxon views and different taxon concepts. We introduce the R package taxlist in the context of object-oriented modelling for taxonomic lists. This package provides a data structure based on species lists in Turboveg, which is a software broadly used for the storage of vegetation-plot databases and implements functions for importing and handling them prior to statistical analysis. We also present a schema for relational databases, compatible with taxlist objects and recommend its use for handling diversity records.

The paper considers the actual problem related to the assessment of the level of anthropogenic load on natural and territorial complexes. Main factors that can be used to describe the nature and level of the anthropogenic load are identified. Their classification is carried out and the representation unification of heterogeneous parameter values is performed. An algorithm for quantitative estimation of the anthropogenic load level and synthesis of the corresponding management decisions is developed. On the basis of the algorithm, a multi-agent computer system for monitoring natural and territorial complexes is implemented. The system allows region leaders to assess the current level of the anthropogenic load, predict its change while constructing new facilities and making appropriate management decisions. An example of a solution to the problem that demonstrates the operability of a monitoring system is presented.

Genetic data represent a relatively new frontier for our understanding of global biodiversity. Ideally, such data should include both organismal DNA‐based genotypes and the ecological context where the organisms were sampled. Yet most tools and standards for data deposition focus exclusively either on genetic or ecological attributes. The Genomic Observatories Metadatabase (GEOME: geome‐db.org) provides an intuitive solution for maintaining links between genetic data sets stored by the International Nucleotide Sequence Database Collaboration (INSDC) and their associated ecological metadata. GEOME facilitates the deposition of raw genetic data to INSDCs sequence read archive (SRA) while maintaining persistent links to standards‐compliant ecological metadata held in the GEOME database. This approach facilitates findable, accessible, interoperable and reusable data archival practices. Moreover, GEOME enables data management solutions for large collaborative groups and expedites batch retrieval of genetic data from the SRA. The article that follows describes how GEOME can enable genuinely open data workflows for researchers in the field of molecular ecology. [ABSTRACT FROM AUTHOR]

Integrated pest management (IPM) guidelines for horticulture are typically established from years of experimental research and experience for a crop species. Ecoinformatics methods can help to quickly adapt these guidelines following major changes in growing practices. Citrus production in California is facing several major challenges, one of which is a shift away from sweet oranges [ Citrus sinensis (L.) Osbeck Sapindales: Rutaceae] toward mandarins (including mostly cultivars of C. reticulata Blanco and C. clementina hort. ex Tanaka). In the absence of IPM guidelines for mandarins, growers are relying on pest information developed from oranges. We mined a database of management records from commercial growers and consultants to determine densities for four arthropod pests: cottony cushion scale (Icerya purchasi Maskell Hemiptera: Monophlebidae), citricola scale (Coccus pseudomagnoliarum Kuwana Hemiptera: Coccidae), European earwig (Forficula auricularia Linnaeus Dermaptera: Forficulidae), citrus red mite (Panonychus citri McGregor Acari: Tetranychidae), and a natural enemy, predatory mites in the genus Euseius (Congdon Acarina: Phytoseiidae). Densities of cottony cushion scale were approximately 10–40 times higher in the two most commonly grown mandarin species than in sweet oranges, suggesting this pest is reaching outbreak levels more often on mandarins. Densities of the other pests and predatory mites did not differ significantly across citrus species. This is a first step toward establishing IPM guidelines for mandarins for these pests; more research is needed to determine how arthropod densities relate to crop performance in mandarins. [ABSTRACT FROM AUTHOR]

Ecologists are increasingly asking large‐scale and/or broad‐scope questions that require vast datasets. In response, various top‐down efforts and incentives have been implemented to encourage data sharing and integration. However, despite general consensus on the critical need for more open ecological data, several roadblocks still discourage compliance and participation in these projects; as a result, ecological data remain largely unavailable. Grassroots initiatives (i.e. efforts initiated and led by cohesive groups of scientists focused on specific goals) have thus far been overlooked as a powerful means to meet these challenges. These bottom‐up collaborative data integration projects can play a crucial role in making high quality datasets available because they tackle the heterogeneity of ecological data at a scale where it is still manageable, all the while offering the support and structure to do so. These initiatives foster best practices in data management and provide tangible rewards to researchers who choose to invest time in sound data stewardship. By maintaining proximity between data generators and data users, grassroots initiatives improve data interpretation and ensure high‐quality data integration while providing fair acknowledgement to data generators. We encourage researchers to formalize existing collaborations and to engage in local activities that improve the availability and distribution of ecological data. By fostering communication and interaction among scientists, we are convinced that grassroots initiatives can significantly support the development of global‐scale data repositories. In doing so, these projects help address important ecological questions and support policy decisions. [ABSTRACT FROM AUTHOR]

The idea that interspecific variation in trophic morphology among closely related species effectively permits resource partitioning has driven research on ecological radiation since Darwin first described variation in beak morphology among Geospiza. Marine turtles comprise an ecological radiation in which interspecific differences in trophic morphology have similarly been implicated as a pathway to ecopartition the marine realm, in both extant and extinct species. Because marine turtles are charismatic flagship species of conservation concern, their trophic ecology has been studied intensively using stable isotope analyses to gain insights into habitat use and diet, principally to inform conservation management. This legion of studies provides an unparalleled opportunity to examine ecological partitioning across numerous hierarchical levels that heretofore has not been applied to any other ecological radiation. Our contribution aims to provide a quantitative analysis of interspecific variation and a comprehensive review of intraspecific variation in trophic ecology across different hierarchical levels marshalling insights about realised trophic ecology derived from stable isotopes. We reviewed 113 stable isotope studies, mostly involving single species, and conducted a meta‐analysis of data from adults to elucidate differences in trophic ecology among species. Our study reveals a more intricate hierarchy of ecopartitioning by marine turtles than previously recognised based on trophic morphology and dietary analyses. We found strong statistical support for interspecific partitioning, as well as a continuum of intraspecific trophic sub‐specialisation in most species across several hierarchical levels. This ubiquity of trophic specialisation across many hierarchical levels exposes a far more complex view of trophic ecology and resource‐axis exploitation than suggested by species diversity alone. Not only do species segregate along many widely understood axes such as body size, macrohabitat, and trophic morphology but the general pattern revealed by isotopic studies is one of microhabitat segregation and variation in foraging behaviour within species, within populations, and among individuals. These findings are highly relevant to conservation management because they imply ecological non‐exchangeability, which introduces a new dimension beyond that of genetic stocks which drives current conservation planning. Perhaps the most remarkable finding from our data synthesis is that four of six marine turtle species forage across several trophic levels. This pattern is unlike that seen in other large marine predators, which forage at a single trophic level according to stable isotopes. This finding affirms suggestions that marine turtles are robust sentinels of ocean health and likely stabilise marine food webs. This insight has broader significance for studies of marine food webs and trophic ecology of large marine predators. Beyond insights concerning marine turtle ecology and conservation, our findings also have broader implications for the study of ecological radiations. Particularly, the unrecognised complexity of ecopartitioning beyond that predicted by trophic morphology suggests that this dominant approach in adaptive radiation research likely underestimates the degree of resource overlap and that interspecific disparities in trophic morphology may often over‐predict the degree of realised ecopartitioning. Hence, our findings suggest that stable isotopes can profitably be applied to study other ecological radiations and may reveal trophic variation beyond that reflected by trophic morphology. [ABSTRACT FROM AUTHOR]

Trait‐based approaches are widespread throughout ecological research as they offer great potential to achieve a general understanding of a wide range of ecological and evolutionary mechanisms. Accordingly, a wealth of trait data is available for many organism groups, but this data is underexploited due to a lack of standardization and heterogeneity in data formats and definitions.We review current initiatives and structures developed for standardizing trait data and discuss the importance of standardization for trait data hosted in distributed open‐access repositories.In order to facilitate the standardization and harmonization of distributed trait datasets by data providers and data users, we propose a standardized vocabulary that can be used for storing and sharing ecological trait data. We discuss potential incentives and challenges for the wide adoption of such a standard by data providers.The use of a standard vocabulary allows for trait datasets from heterogeneous sources to be aggregated more easily into compilations and facilitates the creation of interfaces between software tools for trait‐data handling and analysis. By aiding decentralized trait‐data standardization, our vocabulary may ease data integration and use of trait data for a broader ecological research community and enable global syntheses across a wide range of taxa and ecosystems. [ABSTRACT FROM AUTHOR]

Plants use a variety of mechanisms to defend against herbivore damage, each with different consequences for agricultural production. Crops relying on tolerance strategies may need different pest management approaches versus those relying on resistance strategies. Previous work suggested that densities of fork-tailed bush katydids (Scudderia furcata Brunner von Wattenwyl [Orthoptera: Tettigoniidae]) that generated substantial scarring on cultivars of sweet oranges (Citrus sinensis , (L.) Osbeck [Sapindales: Rutaceae]) produced only low levels of scarring on cultivars of Citrus reticulata Blanco mandarins. We used field experiments in representative cultivars of these species to test non-mutually exclusive hypotheses regarding the mechanisms underlying this observation: 1) katydids are averse to feeding on mandarin fruits, 2) damaged mandarin fruits preferentially abscise, 3) damaged mandarin fruit tissue recovers during development, and 4) katydid scars on mandarins have a different morphology that may result in misclassification. We found strong support for the first hypothesis, demonstrating that katydids reject opportunities to feed on C. reticulata fruit. Instead of chewing deep holes in the fruit, as was commonly observed for C. sinensis , the katydids only scratched the surface of the C. reticulata fruits. The hypotheses of preferential abscission of damaged fruits and of recovery of damaged tissue were not supported. The low incidence of damage to the mandarins prevented a comprehensive assessment of the scar morphology; however, at harvest, the superficial cuts in C. reticulata were not easily distinguishable from background damage. This indicates that in contrast to C. sinensis , C. reticulata has substantial natural resistance to fork-tailed bush katydids making them a non-pest in this crop. [ABSTRACT FROM AUTHOR]

A scientifically informed approach to decision-making is key to ensuring the sustainable management of ecosystems, especially in the light of increasing human pressure on habitats and species. Protected areas, with their long-term institutional mandate for biodiversity conservation, play an important role as data providers, for example, through the long-term monitoring of natural resources. However, poor data management often limits the use and reuse of this wealth of information. In this paper, we share lessons learned in managing long-term data from the Italian Alpine national parks. Our analysis and examples focus on specific issues faced by managers of protected areas, which partially differ from those faced by academic researchers, predominantly owing to different mission, governance, and temporal perspectives. Rigorous data quality control, the use of appropriate data management tools, and acquisition of the necessary skills remain the main obstacles. Common protocols for data collection offer great opportunities for the future, and complete recovery and documentation of time series is an urgent priority. Notably, before data can be shared, protected areas should improve their data management systems, a task that can be achieved only with adequate resources and a long-term vision. We suggest strategies that protected areas, funding agencies, and the scientific community can embrace to address these problems. The added value of our work lies in promoting engagement with managers of protected areas and in reporting and analysing their concrete requirements and problems, thereby contributing to the ongoing discussion on data management and sharing through a bottom-up approach., (© 2023. The Author(s).)

As an increasing variety and complexity of environmental issues confront scientists and natural resource managers, assembling the most relevant and informative data into accessible data systems becomes critical to timely problem solving. Data interoperability is the key criterion for succeeding in that assembly, and much informatics research is focused on data federation, or synthesis to produce interoperable data. However, when candidate data come from numerous, diverse, and high-value legacy data sources, the issue of data variety or heterogeneity can be a significant impediment to interoperability. Research in informatics, computer science and philosophy has frequently focused on resolving data heterogeneity with automation, but subject matter expertise still plays a large role. In particular, human expertise is a large component in the development of tools such as data dictionaries, crosswalks, and ontologies. Such representations may not always match from one data system to another, presenting potentially inconsistent results even with the same data. Here, we use a long-term data set on management actions designed to improve stream habitat for endangered salmon in the Pacific Northwest, to illustrate how different representations can change the underlying information content in the data system.We pass the same data set comprised of 49,619 records through three ontologies, each developed to address a rational management need, and show that the inferences drawn from the data can change with choice of data representation or ontology. One striking example shows that the use of one ontology would suggest water quality improvement projects are the rarest and most expensive restoration actions undertaken, while another will suggest these actions to be the most common and least expensive type of management actions. The discrepancy relates to the origins of the data dictionaries themselves, with one designed to catalog management actions and the other focused on ecological processes. Thus, we argue that in data federation efforts humans are "in the loop" rationally, in the form of the ontologies they have chosen, and diminishing the human component in favor of automation carries risks. Consequently, data federation exercises should be accompanied by validations in order to evaluate and manage those risks. [ABSTRACT FROM AUTHOR]

One of the major challenges facing citrus integrated pest management (IPM) in California is the recent, sharp increase in the acreage of mandarins being planted. The current citrus IPM guidelines have been established from years of experiments and experience in oranges, with no specific guidelines for mandarins. In the absence of research into key arthropod pest effects in mandarins, the assumption that the pest management practices for oranges appropriately transfer for optimal production in mandarins has not been tested. We used a data mining or 'ecoinformatics' approach in which we compiled and analyzed production records collected by growers and pest control advisors to gain an overview of direct pest densities and their relationships with fruit damage for 202 commercial groves, each surveyed for 1–10 yr in the main production region of California. Pest densities were different among four commonly grown species of citrus marketed as mandarins (Citrus reticulata , C. clementina , C. unshiu , and C. tangelo) compared with the standard Citrus sinensis sweet oranges, for fork-tailed bush katydids (Scudderia furcata Brunner von Wattenwyl [Orthoptera: Tettigoniidae]), and citrus thrips (Scirtothrips citri Moulton [Thysanoptera: Thripidae]). Citrus reticulata had notably low levels of fruit damage, suggesting they have natural resistance to direct pests, especially fork-tailed bush katydids. These results suggest that mandarin-specific research and recommendations would improve citrus IPM. More broadly, this is an example of how an ecoinformatics approach can serve as a complement to traditional experimental methods to raise new and unexpected hypotheses that expand our understanding of agricultural systems. [ABSTRACT FROM AUTHOR]

DarkDivNet is a global research collaboration which explores dark diversity — the set of species that are absent from a site despite being suitable under the site conditions and present in the region. Participants of the network survey vascular plant diversity both at local (10  m × 10 m) and regional scales (radius 10 km) using a standardized approach. They also measure simple plant traits and collect soil samples. Observed and dark diversity together form the site‐specific species pool, and the ratio of observed diversity and dark diversity describes community completeness. We shall explore how observed and dark diversity, site‐specific species pool and community completeness vary across natural and anthropogenic gradients. We link plant diversity measures to the information obtained from environmental DNA: soil biota and plant taxa that occurred at the site before. We will refine existing dark diversity methods and use large vegetation databases to infer species habitat suitability. We expand the dark diversity concept from a purely taxonomy‐based approach to include the functional and phylogenetic aspects of diversity. DarkDivNet currently includes 161 planned sampling areas globally, but new participants are welcome. The main vegetation sampling period is scheduled until September 2020, with the first research papers being produced after that. [ABSTRACT FROM AUTHOR]

Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale. We describe sPlot, the first global vegetation‐plot database, containing 1,121,244 plots with plant species lists combined with traits from the TRY database and a global phylogeny. The potential of sPlot is illustrated with the first maps of global patterns of community richness and community‐weighted means of key traits. Rules for data usage, expected impact and limitations of sPlot are discussed. [ABSTRACT FROM AUTHOR]

The Mediterranean fruit fly, Ceratitis capitata (Wied.) (Diptera: Tephritidae) (medfly), is a major pest among all varieties of citrus. Despite advances in recent years, knowledge about the effects of various variables on the spatiotemporal spread of the medfly is still limited. The goal of this study was to characterize the effects of various local and landscape variables on the population density of medfly in citrus orchards in Israel, utilizing the ecoinformatics approach. Data were collected during three citrus growing seasons (years). The medfly population data consisted of a weekly inspection of ~ 2300 traps. Thirteen potentially explanatory variables believed to influence the medfly populations were quantified. The contributions of the explanatory variables were analyzed using multimodel inference. Results show that the medfly population is affected by both local and landscape variables. Further analysis was focused on the data from November (representing the fall peak) and April (representing the beginning of the spring peak). The major findings were: Medfly population was higher in plots that were closer to human communicates, presumably due to their proximity to private gardens; the medfly population was negatively affected by the proportion of the surrounding crop; larger plots with lower perimeter-to-area ratio and plots inside large citrus clusters had smaller populations of medflies; variety had inconsistent effect; and elevation showed inverse response (positive in November and negative in April). Additionally, during the fall peak, the medfly population was positively affected by the proportion of the surrounding deciduous orchards and negatively affected by pest aerial spraying rounds up to a certain number. The results of this study demonstrate that the medfly populations in citrus are affected by the composition of the external landscape. Thus, similar to other studies, this study encourages the adoption of area-wide integrated pest management protocols. [ABSTRACT FROM AUTHOR]

The annual editorial of Phytocoenologia 2019 brings bittersweet news about plot-based vegetation classification. On the one hand, the editorial of our Special Issue "Classification Approaches" (issue 48(2)) reported noticeable gaps in several regions of the world. On the other hand, articles in recent Phytocoenologia reach more and more of these underrepresented regions and extend to previously rarely classified plant formations. Our last issues 48(1-4) included several papers applying vegetation classification to address a number of ecological and socio-economical questions. We highlight the classification of steppe vegetation in Pamir Alai and Tian-Shan Mountains in Middle Asia (Nowak et al. 2018, Phytocoenologia 48: 369-391) and acknowledge the authors with the Editor's Award 2018. Our Ecoinformatics Section attracts many submissions, but we regret that in 2018 we did not publish any paper in the Phytosociological Nomenclature Section. [ABSTRACT FROM AUTHOR]